At present, gesture recognition schemes in a human-machine interaction system are mainly classified into two types: vision-based scheme and sensor-based scheme. Research on the vision-based gesture recognition gets started earlier, the recognizing method is also relatively mature, but this scheme has drawbacks such as sensitivity to environment, complicated system and a large computing amount. The sensor-based gesture recognition gets started later, but it is flexible and reliable, free from influence from environment and light, and easy to implement, and is a recognition method with a development potential. The essence of gesture recognition is to use a gesture recognition algorithm to classify gestures according to a gesture model. Good or bad gesture recognition algorithm directly affect efficiency and precision of the gesture recognition.
Current gesture recognition algorithms mainly comprise the following types:
(1) DTW (Dynamic Time Warping). Although the DTW algorithm can solve the problem about inconsistency of length of an input data sequence and a template data sequence, its matching performance substantially depends on users;
(2) HMM (Hidden Markov Model). Due to users' individual differences, the same gesture action exhibits larger differences, and it is difficult to build an accurate gesture action model and a Hidden Markov Model. Furthermore, and the Hidden Markov Model is too complicated upon analyzing the gesture action so that the computing amount for training and recognition is larger;
(3) Artificial neural network. The artificial neural network recognition algorithm needs a lot of training data, and the algorithm is very complicated.
Hence, application of the current sensor-based recognition scheme to the smart terminal is still confronted with many problems to be solved, for example:
(1) How to achieve higher-precision recognition based on the sensor.
(2) How to reduce complexity in recognition computing. Since the smart terminal is a device with limited resources, and constant sensing of the smart terminal needs to consume much energy during gesture recognition, so the gesture recognition of the smart terminal needs to take computing amount and power consumption into account.
(3) The prior art generally requires operations to be performed on a given smart terminal posture or a fixed plane, limits a scope of user's actions, and imposes higher requirements for apparatus posture. This causes extreme inconvenience to the user's use and produces undesirable user experience.